An Efficient Coding Technique for Stochastic Processes

In the framework of coding theory, under the assumption of a Markov process (Xt) on a finite alphabet A, the compressed representation of the data will be composed of a description of the model used to code the data and the encoded data. Given the model, the Huffman’s algorithm is optimal for the number of bits needed to encode the data. On the other hand, modeling (Xt) through a Partition Markov Model (PMM) promotes a reduction in the number of transition probabilities needed to define the model. This paper shows how the use of Huffman code with a PMM reduces the number of bits needed in this process. We prove the estimation of a PMM allows for estimating the entropy of (Xt), providing an estimator of the minimum expected codeword length per symbol. We show the efficiency of the new methodology on a simulation study and, through a real problem of compression of DNA sequences of SARS-CoV-2, obtaining in the real data at least a reduction of 10.4%.

PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging

Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare. Existing parametric models account only for hand shape, pose, or texture, without modeling the anatomical attributes like bone, which is essential for realistic hand biomechanics analysis. In this paper, we present PIANO, the first parametric bone model of human hands from MRI data. Our PIANO model is biologically correct, simple to animate, and differentiable, achieving more anatomically precise modeling of the inner hand kinematic structure in a data-driven manner than the traditional hand models based on the outer surface only. Furthermore, our PIANO model can be applied in neural network layers to enable training with a fine-grained semantic loss, which opens up the new task of data-driven fine-grained hand bone anatomic and semantic understanding from MRI or even RGB images. We make our model publicly available.

Aromatic Plants from “Plateau des Cataractes”: Kinetic modeling of the extraction of leaf essential oils from Curcuma mangga (Valeton and Zijp) acclimatized in Congo-Brazzaville

Curcuma mangga Val. and Zijp is one of the many underutilized species of the genus Curcuma despite their proven interest as spice to color and enhance the taste of food, on the one hand, and as medicinal plants through essential oils extracted from different parts of the plant, on the other hand. Modeling the extraction in order to optimize the yield of essential oil is a pre requisite for the development of this species used as a spice in Congo-Brazzaville. The experimental results of the extraction of essential oil from the leaves analyzed, according to the phenomenological approach, validate both the kinetic model of the pseudo first order, when the washing step is neglected compared to the diffusion step and that of Peleg corresponding to a desorption in two steps (washing/diffusion). The main constituents of the oil adopt different desorption routes depending on their nature and their quantitative importance in the oil. Simple kinetics have been observed for sesquiterpenes present in relatively large amounts and complex for the monoterpenes in much smaller quantities.

Socio-Scientific Issues and Model-Based Learning

This chapter aims to provide a literature analysis on socio-scientific issues and model-based learning. The position of socio-scientific issues in the process of raising science literate students is indisputable. On the other hand, modeling gives students opportunities to construct their own models and use them through the learning process to formulate hypothesis, make investigations, explain scientific phenomena, and communicate and justify their ideas. Therefore, embedding modeling practice to SSI-based instruction through a framework is an innovative tool for scientific literacy in science education.

Hall Amplifier Nanoscale Device (HAND): Modeling, Simulations and Feasibility Analysis for THz Sensor

HAND (Hall Amplifier Nanoscale Device), a new nano-metric device, was designed, simulated, and modeled for feasibility analysis, with the challenge of combining a well-known macro effect into the nanoscale world. HAND is based on the well-known Hall Effect, and it may enable circuitry working at very high frequencies (tens of Tera-Hertz). The architecture, design, and simulations were performed while using Comsol Multi-Physics Package Software. Complementary accurate analytical models were developed to support the understanding of the device functionality, including treatment of specific phenomena, such as heat transfer, and mega-magnet feasibility inside integrated circuits. This new device, combining both the Hall Effect and nanoscale dimensions, holds the potential to change the computing rates in the microelectronics circuitry world, and can serve as a game changer.